Metadata assisted Management of Diabetes in Rural Health Disparity Communities

Diabetes is an epidemic disease in the United States and worldwide. Diabetes care accounts for 10% of all U.S. healthcare costs, most of which is consumed in the care of complications from diabetes, but also includes lost economic productivity from illness, disability and blindness. Despite the high incidence of diabetes, low health literacy and limited access to health care resources keeps families in a cycle of poor health that continues from generation to generation. Critical socio-economic and geographical barriers to health care in rural, health disparity communities pose unique challenges to identify those patients at the greatest risk for complications of diabetes, which are not met by current health care delivery models. As an emerging technology, telemedicine is an efficient and cost-effective way to deliver health care services over large geographic regions including rural, health disparity communities. Hubble Telemedical provides remote management of diabetic retinopathy using retinal images acquired in the primary care practice space, through its award winning TRIAD Network. Hubble & #39;s network leverages image and metadata analysis algorithms and the connectivity to the Internet to provide a scalable, web-based, and cost effective solution for high throughput, point-of-care assessment and management of diabetic disease complications in large health disparity populations. The result? Improved efficiency and health outcomes. This proposal will leverage an ongoing partnership with the Delta Health Alliance (Stoneville, MS) and the University of Tennessee Health Science Center to implement a translational, informatics-based diabetes management program. In our Phase I study we developed a proprietary software interface to automatically acquire remote electronic health record data and established the feasibility of using clinical metadata mining to identify and more effectively manage those patients at highest risk for the complications of diabetic retinopathy. Our goal is to identify and target high-risk patients for medical intervention and referral as a cost-effective approach to improving health outcomes in rural America. In this Phase II study, Hubble Telemedical and its partners will demonstrate that metadata-based health care analytics can be provided to rural communities to effect a scalable and cost effective solution to diabetes management and disease progression. We will demonstrate improved and cost effective health care outcomes in at risk patients in a cohort of over 800 patients using data mining analysis. In Phase III, Hubble will deploy the developed system to a multiplicity of rural, health disparity communities throughout the US in partnership with its managed care and wellness partners to apply this novel paradigm to optimize management of diabetes, obesity and their complications in rural America to help curb the spiraling costs of US health care using a cost effective data mining model.